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[default]
package=scorings
########################################
# scoring methods for classification
########################################
[accuracy_score]
subpackage = classification
module = Accuracy
class = AccuracyScoring
[precision_score]
subpackage = classification
module = Precision
class = PrecisionScoring
[recall_score]
subpackage = classification
module = Recall
class = RecallScoring
[f1_score]
subpackage = classification
module = F1
class = F1Scoring
[roc_auc_score]
subpackage = classification
module = ROCAUC
class = ROCAUCScoring
[confusion_matrix]
subpackage = classification
module = ConfusionMatrix
class = ConfusionMatrixScoring
[roc_curve]
subpackage = classification
module = ROCCurve
class = ROCCurveScoring
[precision_recall_fscore_support]
subpackage = classification
module = PrecisionRecallFscoreSupport
class = PrecisionRecallFscoreSupportScoring
###########################################
# scoring methods for clustering
###########################################
[silhouette_score]
subpackage = clustering
module = Silhouette
class = SilhouetteScoring
########################################
# scoring methods for regression
########################################
[r2_score]
subpackage = regression
module = R2
class = R2Scoring
[mean_squared_error]
subpackage = regression
module = MeanSquaredError
class = MeanSquaredErrorScoring
[mean_absolute_error]
subpackage = regression
module = MeanAbsoluteError
class = MeanAbsoluteErrorScoring
[explained_variance_score]
subpackage = regression
module = ExplainedVariance
class = ExplainedVarianceScoring
###########################################
# scoring methods for statistical testing
###########################################
[normaltest]
subpackage = statstest
module = NormalTest
class = NormalTestScoring
[ttest_1samp]
subpackage = statstest
module = TTest1Samp
class = TTestOneSampleScoring
[f_oneway]
subpackage = statstest
module = FOneway
class = FOnewayScoring
[adfuller]
subpackage = statstest
module = Adfuller
class = AdfullerScoring
[kpss]
subpackage = statstest
module = KPSS
class = KPSSScoring
[kstest]
subpackage = statstest
module = KSTest
class = KSTestScoring
[mannwhitneyu]
subpackage = statstest
module = MannWhitneyU
class = MannWhitneyUScoring
[wilcoxon]
subpackage = statstest
module = Wilcoxon
class = WilcoxonScoring
[ttest_ind]
subpackage = statstest
module = TTestInd
class = TTestTwoIndSampleScoring
[ttest_rel]
subpackage = statstest
module = TTestRel
class = TTestTwoSampleScoring
[ks_2samp]
subpackage = statstest
module = KSTest2Samp
class = KSTest2SampleScoring
[wasserstein_distance]
subpackage = statstest
module = WassersteinDistance
class = WassersteinDistanceScoring
[energy_distance]
subpackage = statstest
module = EnergyDistance
class = EnergyDistanceScoring
[anova]
subpackage = statstest
module = Anova
class = AnovaTableScoring
#############################################
# scoring methods for statistical functions
#############################################
[describe]
subpackage = statsfunctions
module = Describe
class = DescribeScoring
[moment]
subpackage = statsfunctions
module = Moment
class = MomentScoring
[tmean]
subpackage = statsfunctions
module = TMean
class = TMeanScoring
[tvar]
subpackage = statsfunctions
module = TVar
class = TVarScoring
[trim]
subpackage = statsfunctions
module = Trim
class = TrimScoring
[pearsonr]
subpackage = statsfunctions
module = Pearsonr
class = PearsonrScoring
[spearmanr]
subpackage = statsfunctions
module = Spearmanr
class = SpearmanrScoring
###########################################
# scoring methods for pairwise distances
###########################################
[pairwise_distances]
subpackage = pairwise
module = PairwiseDistances
class = PairwiseDistancesScoring